Detection and Biopsy Guidance of Nasopharyngeal Carcinoma Based on Artificial Intelligence and Endoscopic Images

Recruiting

• Conditions: Nasopharyngeal Carcinoma; Image-Guided Biopsy
• Interventions: Diagnostic Test: Nasopharyngeal Endoscopy image-guided Biopsy

• Registration Number: NCT05202626
• Lead Sponsor: Chinese Academy of Sciences

Brief Summary

Due to the occult anatomic location of the nasopharynx and frequent presence of adenoid hyperplasia, the positive rate for nasopharyngeal carcinoma identification during biopsy is low, thus leading to delayed or missed diagnosis for nasopharyngeal carcinoma upon initial attempt. Here, we aimed to develop an artificial intelligence tool to detect nasopharyngeal malignancies and guide biopsy under endoscopic examination based on deep learning.

Detailed Description

Due to the occult anatomic location of the nasopharynx and frequent presence of adenoid hyperplasia, the positive rate for nasopharyngeal carcinoma identification during biopsy is low, thus leading to delayed or missed diagnosis for nasopharyngeal carcinoma upon initial attempt. Here, we aimed to develop an artificial intelligence tool to detect nasopharyngeal malignancies and guide biopsy under endoscopic examination based on deep learning.

Study Timeline

• Study Start: 2021-12-01
• Study First Submitted: 2022-01-09
• Study First Submitted QC: 2022-01-09
• Study First Posted: 2022-01-21
• Status Verified: 2023-10
• Last Update Submitted: 2023-10-13
• Last Update Posted: 2023-10-17
• Primary Completion: 2023-10-30
• Study Completion: 2025-06-28

Recruitment & Eligibility

• Status: RECRUITING
• Sex: All
• Target Recruitment: 100

Inclusion Criteria

• The patient was found to have a nasopharyngeal lesion through the nasopharyngeal endoscopy and the clinicans considered it necessary to perform an biopsy.
• Hemilateral lesion with limited size.

Exclusion Criteria

• Patients with nasopharyngeal cancer, oropharyngeal cancer, hypopharyngeal cancer, etc. who have already been treated.

Study & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Arm && Interventions

Group	Intervention	Description
Fujian Provincial Cancer Hospital	Nasopharyngeal Endoscopy image-guided Biopsy	The participant who is found to have a nasopharyngeal lesion through the nasopharyngeal endoscopy in Fujian Provincial Cancer Hospital. The physicians in Fujian Provincial Cancer Hospital consider it necessary to perform an endoscopic image-guided biopsy.
Sun Yat-Sen University Cancer Center	Nasopharyngeal Endoscopy image-guided Biopsy	The participant who is found to have a nasopharyngeal lesion through the nasopharyngeal endoscopy in Sun Yat-Sen University Cancer Center. The physicians in Sun Yat-Sen University Cancer Center consider it necessary to perform an endoscopic image-guided biopsy.
Nanfang Hospital, Southern Medical University	Nasopharyngeal Endoscopy image-guided Biopsy	The participant who is found to have a nasopharyngeal lesion through the nasopharyngeal endoscopy in Nanfang Hospital. The physicians in Nanfang Hospital consider it necessary to perform an endoscopic image-guided biopsy.
Guangdong Provincial People's Hospital	Nasopharyngeal Endoscopy image-guided Biopsy	The participant who is found to have a nasopharyngeal lesion through the nasopharyngeal endoscopy in Guangdong Provincial People's Hospital. The physicians in Guangdong Provincial People's Hospital consider it necessary to perform an endoscopic image-guided biopsy.
Hainan Provincial People's Hospital	Nasopharyngeal Endoscopy image-guided Biopsy	The participant who is found to have a nasopharyngeal lesion through the nasopharyngeal endoscopy in Hainan Provincial People's Hospital. The physicians in Hainan Provincial People's Hospital consider it necessary to perform an endoscopic image-guided biopsy.

Primary Outcome Measures

Name	Time	Method
Aera under the receiver operating characteristic curve (AUC)	three months	AUC of an deep learning-based model in discriminating nasopharyngeal carcinoma from bengin lesion.

Secondary Outcome Measures

Name	Time	Method
Accuray	three months	The agreement between the deep learning-based model and the histopathological diagnosis of the three biopsy specimens (inside the lesion, 5-8 mm outside the lesion, and 8-10 mm outside the lesion).

Trial Locations

Locations (5)

Guangdong Provincial People's Hospital; 🇨🇳 Guangzhou, Guangdong, China

Sun Yat-Sen University Cancer Center; 🇨🇳 Guangzhou, Guangdong, China

Fujian Provincial Cancer Hospital; 🇨🇳 Fuzhou, Fujian, China

Hainan Provincial People's Hospital; 🇨🇳 Haikou, Hainan, China

Nanfang Hospital, Southern Medical University; 🇨🇳 Guangzhou, Guangdong, China